--- permalink: python/v3/waterfall-charts/ description: How to make waterfall plots in Python with Plotly. name: Waterfall Charts thumbnail: thumbnail/waterfall-charts.jpg language: python/v3 display_as: basic order: 13 ipynb: /~notebook_demo/276 layout: base page_type: u-guide --- {% raw %}
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import plotly
plotly.__version__
import plotly.offline as py
import plotly.graph_objs as go
py.init_notebook_mode(connected = False)
trace = go.Waterfall(
name = "20", orientation = "v",
measure = ["relative", "relative", "total", "relative", "relative", "total"],
x = ["Sales", "Consulting", "Net revenue", "Purchases", "Other expenses", "Profit before tax"],
textposition = "outside",
text = ["+60", "+80", "", "-40", "-20", "Total"],
y = [60, 80, 0, -40, -20, 0],
connector = {"line":{"color":"rgb(63, 63, 63)"}},
)
layout = go.Layout(
title = "Profit and loss statement 2018",
showlegend = True
)
py.iplot(go.Figure([trace], layout), filename = "basic_waterfall_chart")
This example uses the waterfallgroupgap attribute, which sets a gap between bars.
import plotly.offline as py
import plotly.graph_objs as go
py.init_notebook_mode(connected = False)
trace1 = go.Waterfall(
x = [["2016", "2017", "2017", "2017", "2017", "2018", "2018", "2018", "2018"],
["initial", "q1", "q2", "q3", "total", "q1", "q2", "q3", "total"]],
measure = ["absolute", "relative", "relative", "relative", "total", "relative", "relative", "relative", "total"],
y = [1, 2, 3, -1, None, 1, 2, -4, None],
base = 1000
)
trace2 = go.Waterfall(
x = [["2016", "2017", "2017", "2017", "2017", "2018", "2018", "2018", "2018"],
["initial", "q1", "q2", "q3", "total", "q1", "q2", "q3", "total"]],
measure = ["absolute", "relative", "relative", "relative", "total", "relative", "relative", "relative", "total"],
y = [1.1, 2.2, 3.3, -1.1, None, 1.1, 2.2, -4.4, None],
base = 1000
)
layout = go.Layout(
waterfallgroupgap = 0.5,
xaxis = {"title":"MULTI-CATEGORY","tickfont":{"size":16},"ticks":"outside"}
)
data = [trace1,trace2]
fig = go.Figure(data, layout)
py.iplot(fig,filename = "mutli_category_waterfall")
This example uses decreasing, increasing, and total attributes to customize the bars.
import plotly.offline as py
import plotly.graph_objs as go
py.init_notebook_mode(connected = False)
trace = go.Waterfall(
x = [["2016", "2017", "2017", "2017", "2017", "2018", "2018", "2018", "2018"],
["initial", "q1", "q2", "q3", "total", "q1", "q2", "q3", "total"]],
measure = ["absolute", "relative", "relative", "relative", "total", "relative", "relative", "relative", "total"],
y = [10, 20, 30, -10, None, 10, 20, -40, None], base = 300,
decreasing = {"marker":{"color":"Maroon", "line":{"color":"red", "width":2}}},
increasing = {"marker":{"color":"Teal"}},
totals = {"marker":{"color":"deep sky blue", "line":{"color":'blue', "width":3}}}
)
layout = go.Layout(
title = "Profit and loss statement",
waterfallgap = 0.3,
xaxis = {"title":"", "tickfont":{"size":15}, "ticks":"outside"}
)
py.iplot(go.Figure([trace], layout), filename = "Style_waterfall")
import plotly.offline as py
import plotly.graph_objs as go
py.init_notebook_mode(connected = False)
trace = go.Waterfall(
name = "2018", orientation = "h", measure = ["relative", "relative", "relative", "relative", "total", "relative",
"relative", "relative", "relative", "total", "relative", "relative", "total", "relative", "total"],
y = ["Sales", "Consulting", "Maintenance", "Other revenue", "Net revenue", "Purchases", "Material expenses",
"Personnel expenses", "Other expenses", "Operating profit", "Investment income", "Financial income",
"Profit before tax", "Income tax (15%)", "Profit after tax"],
x = [375, 128, 78, 27, None, -327, -12, -78, -12, None, 32, 89, None, -45, None],
connector = {"mode":"between", "line":{"width":4, "color":"rgb(0, 0, 0)", "dash":"solid"}}
)
layout = go.Layout(
title = "Profit and loss statement 2018<br>waterfall chart displaying positive and negative",
yaxis = {"type":"category", "autorange":"reversed"},
xaxis = {"type":"linear"},
margin = {"l":150},
showlegend = True
)
py.iplot(go.Figure([trace], layout), filename = "horizontal_waterfall")
See https://plotly.com/python/reference/#waterfall for more information and chart attribute options!